Pathway Summary

Consort map

Demographic information

Characteristic

N

Overall, N = 1181

control, N = 591

treatment, N = 591

p-value2

age

116

50.73 ± 13.01 (25 - 74)

50.35 ± 13.01 (25 - 74)

51.09 ± 13.11 (28 - 73)

0.763

Unknown

2

2

0

gender

118

0.827

f

91 (77%)

45 (76%)

46 (78%)

m

27 (23%)

14 (24%)

13 (22%)

occupation

118

0.622

day_training

2 (1.7%)

2 (3.4%)

0 (0%)

full_time

14 (12%)

7 (12%)

7 (12%)

homemaker

11 (9.3%)

5 (8.5%)

6 (10%)

other

2 (1.7%)

0 (0%)

2 (3.4%)

part_time

19 (16%)

9 (15%)

10 (17%)

retired

33 (28%)

15 (25%)

18 (31%)

self_employ

4 (3.4%)

2 (3.4%)

2 (3.4%)

student

2 (1.7%)

0 (0%)

2 (3.4%)

t_and_e

2 (1.7%)

1 (1.7%)

1 (1.7%)

unemploy

29 (25%)

18 (31%)

11 (19%)

marital

118

0.889

cohabitation

1 (0.8%)

0 (0%)

1 (1.7%)

divore

11 (9.3%)

7 (12%)

4 (6.8%)

in_relationship

3 (2.5%)

2 (3.4%)

1 (1.7%)

married

32 (27%)

16 (27%)

16 (27%)

none

61 (52%)

29 (49%)

32 (54%)

seperation

3 (2.5%)

2 (3.4%)

1 (1.7%)

widow

7 (5.9%)

3 (5.1%)

4 (6.8%)

edu

118

0.349

bachelor

27 (23%)

10 (17%)

17 (29%)

diploma

22 (19%)

15 (25%)

7 (12%)

hd_ad

3 (2.5%)

2 (3.4%)

1 (1.7%)

postgraduate

11 (9.3%)

5 (8.5%)

6 (10%)

primary

8 (6.8%)

2 (3.4%)

6 (10%)

secondary_1_3

15 (13%)

8 (14%)

7 (12%)

secondary_4_5

27 (23%)

15 (25%)

12 (20%)

secondary_6_7

5 (4.2%)

2 (3.4%)

3 (5.1%)

fam_income

118

0.972

10001_12000

5 (4.2%)

2 (3.4%)

3 (5.1%)

12001_14000

5 (4.2%)

2 (3.4%)

3 (5.1%)

14001_16000

6 (5.1%)

2 (3.4%)

4 (6.8%)

16001_18000

3 (2.5%)

1 (1.7%)

2 (3.4%)

18001_20000

4 (3.4%)

3 (5.1%)

1 (1.7%)

20001_above

22 (19%)

12 (20%)

10 (17%)

2001_4000

18 (15%)

10 (17%)

8 (14%)

4001_6000

12 (10%)

5 (8.5%)

7 (12%)

6001_8000

10 (8.5%)

6 (10%)

4 (6.8%)

8001_10000

9 (7.6%)

4 (6.8%)

5 (8.5%)

below_2000

24 (20%)

12 (20%)

12 (20%)

medication

118

105 (89%)

53 (90%)

52 (88%)

0.769

onset_duration

116

15.05 ± 10.40 (0 - 56)

16.10 ± 11.34 (1 - 56)

13.97 ± 9.31 (0 - 35)

0.272

Unknown

2

0

2

onset_age

114

35.80 ± 14.55 (10 - 65)

34.04 ± 13.33 (10 - 61)

37.55 ± 15.60 (14 - 65)

0.200

Unknown

4

2

2

1Mean ± SD (Range); n (%)

2Two Sample t-test; Pearson's Chi-squared test; Fisher's exact test

Measurement

Table

Characteristic

N

Overall, N = 1181

control, N = 591

treatment, N = 591

p-value2

recovery_stage_a

118

3.17 ± 1.20 (1 - 5)

3.29 ± 1.26 (1 - 5)

3.05 ± 1.14 (1 - 5)

0.285

recovery_stage_b

118

17.88 ± 2.68 (9 - 24)

17.86 ± 2.69 (9 - 23)

17.90 ± 2.70 (13 - 24)

0.946

ras_confidence

118

30.14 ± 4.98 (18 - 45)

29.97 ± 4.32 (19 - 40)

30.32 ± 5.60 (18 - 45)

0.700

ras_willingness

118

11.94 ± 2.02 (7 - 15)

11.88 ± 1.86 (8 - 15)

12.00 ± 2.18 (7 - 15)

0.751

ras_goal

118

17.36 ± 3.13 (11 - 25)

17.36 ± 2.84 (12 - 24)

17.37 ± 3.42 (11 - 25)

0.977

ras_reliance

118

13.34 ± 2.84 (7 - 20)

13.22 ± 2.64 (8 - 18)

13.46 ± 3.04 (7 - 20)

0.652

ras_domination

118

10.02 ± 2.33 (3 - 15)

10.32 ± 2.21 (3 - 15)

9.71 ± 2.43 (3 - 15)

0.156

symptom

118

29.99 ± 9.62 (14 - 56)

30.12 ± 9.71 (14 - 55)

29.86 ± 9.62 (15 - 56)

0.887

slof_work

118

22.31 ± 4.75 (10 - 30)

22.42 ± 4.25 (13 - 30)

22.19 ± 5.24 (10 - 30)

0.788

slof_relationship

118

25.41 ± 5.90 (11 - 35)

24.95 ± 5.65 (13 - 35)

25.86 ± 6.16 (11 - 35)

0.402

satisfaction

118

20.58 ± 7.02 (5 - 35)

19.76 ± 6.51 (5 - 31)

21.41 ± 7.46 (5 - 35)

0.205

mhc_emotional

118

11.10 ± 3.86 (3 - 18)

10.81 ± 3.72 (3 - 17)

11.39 ± 4.01 (4 - 18)

0.420

mhc_social

118

15.15 ± 5.56 (5 - 30)

15.20 ± 5.55 (7 - 30)

15.10 ± 5.62 (5 - 29)

0.921

mhc_psychological

118

21.96 ± 6.45 (6 - 36)

21.69 ± 5.91 (9 - 36)

22.22 ± 7.00 (6 - 36)

0.660

resilisnce

118

16.67 ± 4.65 (6 - 30)

16.20 ± 4.19 (6 - 24)

17.14 ± 5.06 (7 - 30)

0.278

social_provision

118

13.73 ± 2.84 (5 - 20)

13.36 ± 2.36 (8 - 20)

14.10 ± 3.22 (5 - 20)

0.154

els_value_living

118

17.02 ± 3.07 (5 - 25)

16.68 ± 2.68 (8 - 22)

17.36 ± 3.41 (5 - 25)

0.233

els_life_fulfill

118

12.74 ± 3.40 (4 - 20)

12.19 ± 3.17 (5 - 19)

13.29 ± 3.56 (4 - 20)

0.078

els

118

29.75 ± 5.94 (9 - 45)

28.86 ± 5.12 (17 - 38)

30.64 ± 6.58 (9 - 45)

0.104

social_connect

118

26.42 ± 9.24 (8 - 48)

27.14 ± 8.68 (8 - 45)

25.69 ± 9.80 (8 - 48)

0.400

shs_agency

118

14.40 ± 5.11 (3 - 24)

14.05 ± 4.66 (3 - 21)

14.75 ± 5.55 (3 - 24)

0.463

shs_pathway

118

16.31 ± 4.00 (4 - 24)

16.10 ± 3.71 (8 - 24)

16.51 ± 4.28 (4 - 24)

0.583

shs

118

30.70 ± 8.71 (7 - 48)

30.15 ± 8.02 (13 - 45)

31.25 ± 9.39 (7 - 48)

0.494

esteem

118

12.61 ± 1.67 (10 - 20)

12.75 ± 1.61 (10 - 18)

12.47 ± 1.74 (10 - 20)

0.381

mlq_search

118

14.80 ± 3.58 (3 - 21)

14.71 ± 3.31 (6 - 21)

14.88 ± 3.86 (3 - 21)

0.798

mlq_presence

118

13.40 ± 4.28 (3 - 21)

13.34 ± 3.81 (5 - 21)

13.46 ± 4.73 (3 - 21)

0.881

mlq

118

28.19 ± 6.99 (6 - 42)

28.05 ± 6.09 (12 - 40)

28.34 ± 7.84 (6 - 42)

0.824

empower

118

19.31 ± 4.37 (6 - 30)

19.03 ± 4.13 (11 - 30)

19.59 ± 4.63 (6 - 30)

0.490

ismi_resistance

118

14.57 ± 2.62 (5 - 20)

14.47 ± 2.16 (10 - 20)

14.66 ± 3.03 (5 - 20)

0.701

ismi_discrimation

118

11.45 ± 3.21 (5 - 20)

12.02 ± 3.08 (5 - 20)

10.88 ± 3.26 (5 - 20)

0.054

sss_affective

118

10.02 ± 3.53 (3 - 18)

10.22 ± 3.38 (3 - 18)

9.81 ± 3.69 (3 - 18)

0.534

sss_behavior

118

9.68 ± 3.77 (3 - 18)

10.07 ± 3.83 (3 - 18)

9.29 ± 3.69 (3 - 18)

0.263

sss_cognitive

118

8.13 ± 3.67 (3 - 18)

8.34 ± 3.72 (3 - 18)

7.92 ± 3.64 (3 - 18)

0.533

sss

118

27.82 ± 10.06 (9 - 54)

28.63 ± 9.94 (9 - 54)

27.02 ± 10.20 (9 - 54)

0.387

1Mean ± SD (Range)

2Two Sample t-test

Plot

## Warning: Removed 2 rows containing non-finite values (`stat_density()`).
## Warning: Removed 1 rows containing missing values (`geom_vline()`).

Data analysis

Table

Group

Characteristic

Beta

SE1

95% CI1

p-value

recovery_stage_a

(Intercept)

3.29

0.152

2.99, 3.59

group

control

—

—

—

treatment

-0.237

0.215

-0.658, 0.183

0.271

time_point

1st

—

—

—

2nd

0.043

0.240

-0.428, 0.514

0.859

group * time_point

treatment * 2nd

0.508

0.342

-0.163, 1.18

0.142

Pseudo R square

0.024

recovery_stage_b

(Intercept)

17.9

0.365

17.1, 18.6

group

control

—

—

—

treatment

0.034

0.516

-0.978, 1.05

0.948

time_point

1st

—

—

—

2nd

-0.281

0.542

-1.34, 0.780

0.605

group * time_point

treatment * 2nd

0.788

0.772

-0.725, 2.30

0.310

Pseudo R square

0.007

ras_confidence

(Intercept)

30.0

0.663

28.7, 31.3

group

control

—

—

—

treatment

0.356

0.938

-1.48, 2.19

0.705

time_point

1st

—

—

—

2nd

0.726

0.755

-0.753, 2.20

0.340

group * time_point

treatment * 2nd

1.06

1.077

-1.05, 3.17

0.327

Pseudo R square

0.019

ras_willingness

(Intercept)

11.9

0.265

11.4, 12.4

group

control

—

—

—

treatment

0.119

0.374

-0.615, 0.852

0.752

time_point

1st

—

—

—

2nd

-0.643

0.299

-1.23, -0.057

0.035

group * time_point

treatment * 2nd

0.833

0.427

-0.004, 1.67

0.056

Pseudo R square

0.020

ras_goal

(Intercept)

17.4

0.419

16.5, 18.2

group

control

—

—

—

treatment

0.017

0.592

-1.14, 1.18

0.977

time_point

1st

—

—

—

2nd

-0.446

0.502

-1.43, 0.539

0.378

group * time_point

treatment * 2nd

1.65

0.716

0.249, 3.06

0.024

Pseudo R square

0.023

ras_reliance

(Intercept)

13.2

0.369

12.5, 13.9

group

control

—

—

—

treatment

0.237

0.523

-0.787, 1.26

0.650

time_point

1st

—

—

—

2nd

0.327

0.405

-0.466, 1.12

0.422

group * time_point

treatment * 2nd

1.04

0.577

-0.088, 2.17

0.075

Pseudo R square

0.035

ras_domination

(Intercept)

10.3

0.297

9.74, 10.9

group

control

—

—

—

treatment

-0.610

0.420

-1.43, 0.214

0.149

time_point

1st

—

—

—

2nd

-0.315

0.426

-1.15, 0.519

0.462

group * time_point

treatment * 2nd

1.39

0.607

0.201, 2.58

0.025

Pseudo R square

0.027

symptom

(Intercept)

30.1

1.253

27.7, 32.6

group

control

—

—

—

treatment

-0.254

1.773

-3.73, 3.22

0.886

time_point

1st

—

—

—

2nd

-0.151

1.096

-2.30, 2.00

0.891

group * time_point

treatment * 2nd

-1.40

1.564

-4.46, 1.67

0.375

Pseudo R square

0.004

slof_work

(Intercept)

22.4

0.618

21.2, 23.6

group

control

—

—

—

treatment

-0.237

0.873

-1.95, 1.47

0.786

time_point

1st

—

—

—

2nd

-0.191

0.657

-1.48, 1.10

0.772

group * time_point

treatment * 2nd

0.304

0.937

-1.53, 2.14

0.747

Pseudo R square

0.000

slof_relationship

(Intercept)

24.9

0.764

23.5, 26.4

group

control

—

—

—

treatment

0.915

1.080

-1.20, 3.03

0.398

time_point

1st

—

—

—

2nd

-1.15

0.775

-2.67, 0.367

0.143

group * time_point

treatment * 2nd

1.85

1.105

-0.319, 4.01

0.100

Pseudo R square

0.021

satisfaction

(Intercept)

19.8

0.921

18.0, 21.6

group

control

—

—

—

treatment

1.64

1.303

-0.909, 4.20

0.209

time_point

1st

—

—

—

2nd

0.668

1.073

-1.43, 2.77

0.536

group * time_point

treatment * 2nd

0.411

1.531

-2.59, 3.41

0.789

Pseudo R square

0.019

mhc_emotional

(Intercept)

10.8

0.497

9.84, 11.8

group

control

—

—

—

treatment

0.576

0.703

-0.802, 1.95

0.414

time_point

1st

—

—

—

2nd

0.353

0.506

-0.639, 1.35

0.488

group * time_point

treatment * 2nd

-0.220

0.723

-1.64, 1.20

0.762

Pseudo R square

0.005

mhc_social

(Intercept)

15.2

0.746

13.7, 16.7

group

control

—

—

—

treatment

-0.102

1.055

-2.17, 1.97

0.923

time_point

1st

—

—

—

2nd

0.571

0.878

-1.15, 2.29

0.518

group * time_point

treatment * 2nd

-0.232

1.253

-2.69, 2.22

0.854

Pseudo R square

0.002

mhc_psychological

(Intercept)

21.7

0.869

20.0, 23.4

group

control

—

—

—

treatment

0.525

1.229

-1.88, 2.93

0.670

time_point

1st

—

—

—

2nd

0.732

0.992

-1.21, 2.68

0.463

group * time_point

treatment * 2nd

-0.062

1.415

-2.84, 2.71

0.965

Pseudo R square

0.004

resilisnce

(Intercept)

16.2

0.592

15.0, 17.4

group

control

—

—

—

treatment

0.932

0.838

-0.709, 2.57

0.268

time_point

1st

—

—

—

2nd

0.158

0.715

-1.24, 1.56

0.826

group * time_point

treatment * 2nd

1.42

1.020

-0.574, 3.42

0.167

Pseudo R square

0.034

social_provision

(Intercept)

13.4

0.374

12.6, 14.1

group

control

—

—

—

treatment

0.746

0.528

-0.290, 1.78

0.160

time_point

1st

—

—

—

2nd

-0.617

0.470

-1.54, 0.304

0.194

group * time_point

treatment * 2nd

0.761

0.670

-0.553, 2.07

0.260

Pseudo R square

0.034

els_value_living

(Intercept)

16.7

0.407

15.9, 17.5

group

control

—

—

—

treatment

0.678

0.575

-0.450, 1.81

0.241

time_point

1st

—

—

—

2nd

0.234

0.484

-0.714, 1.18

0.630

group * time_point

treatment * 2nd

0.293

0.690

-1.06, 1.65

0.673

Pseudo R square

0.018

els_life_fulfill

(Intercept)

12.2

0.432

11.3, 13.0

group

control

—

—

—

treatment

1.10

0.611

-0.096, 2.30

0.074

time_point

1st

—

—

—

2nd

0.580

0.411

-0.225, 1.39

0.163

group * time_point

treatment * 2nd

-0.257

0.586

-1.41, 0.892

0.663

Pseudo R square

0.027

els

(Intercept)

28.9

0.773

27.3, 30.4

group

control

—

—

—

treatment

1.78

1.093

-0.363, 3.92

0.106

time_point

1st

—

—

—

2nd

0.795

0.751

-0.677, 2.27

0.294

group * time_point

treatment * 2nd

0.038

1.071

-2.06, 2.14

0.972

Pseudo R square

0.026

social_connect

(Intercept)

27.1

1.221

24.7, 29.5

group

control

—

—

—

treatment

-1.44

1.727

-4.83, 1.94

0.406

time_point

1st

—

—

—

2nd

1.22

1.217

-1.17, 3.60

0.321

group * time_point

treatment * 2nd

-3.62

1.737

-7.03, -0.220

0.041

Pseudo R square

0.027

shs_agency

(Intercept)

14.1

0.665

12.7, 15.4

group

control

—

—

—

treatment

0.695

0.940

-1.15, 2.54

0.461

time_point

1st

—

—

—

2nd

0.058

0.684

-1.28, 1.40

0.933

group * time_point

treatment * 2nd

0.825

0.976

-1.09, 2.74

0.402

Pseudo R square

0.012

shs_pathway

(Intercept)

16.1

0.517

15.1, 17.1

group

control

—

—

—

treatment

0.407

0.730

-1.02, 1.84

0.579

time_point

1st

—

—

—

2nd

0.104

0.529

-0.932, 1.14

0.845

group * time_point

treatment * 2nd

0.034

0.754

-1.44, 1.51

0.965

Pseudo R square

0.003

shs

(Intercept)

30.2

1.127

27.9, 32.4

group

control

—

—

—

treatment

1.10

1.594

-2.02, 4.23

0.491

time_point

1st

—

—

—

2nd

0.170

1.110

-2.00, 2.35

0.879

group * time_point

treatment * 2nd

0.832

1.584

-2.27, 3.94

0.601

Pseudo R square

0.008

esteem

(Intercept)

12.7

0.203

12.3, 13.1

group

control

—

—

—

treatment

-0.271

0.287

-0.833, 0.291

0.346

time_point

1st

—

—

—

2nd

-0.014

0.310

-0.622, 0.593

0.963

group * time_point

treatment * 2nd

0.250

0.442

-0.616, 1.12

0.574

Pseudo R square

0.006

mlq_search

(Intercept)

14.7

0.459

13.8, 15.6

group

control

—

—

—

treatment

0.169

0.649

-1.10, 1.44

0.794

time_point

1st

—

—

—

2nd

0.158

0.604

-1.03, 1.34

0.795

group * time_point

treatment * 2nd

-0.159

0.862

-1.85, 1.53

0.854

Pseudo R square

0.001

mlq_presence

(Intercept)

13.3

0.552

12.3, 14.4

group

control

—

—

—

treatment

0.119

0.781

-1.41, 1.65

0.879

time_point

1st

—

—

—

2nd

0.260

0.639

-0.993, 1.51

0.686

group * time_point

treatment * 2nd

0.099

0.912

-1.69, 1.89

0.914

Pseudo R square

0.001

mlq

(Intercept)

28.1

0.911

26.3, 29.8

group

control

—

—

—

treatment

0.288

1.288

-2.24, 2.81

0.823

time_point

1st

—

—

—

2nd

0.428

1.101

-1.73, 2.59

0.699

group * time_point

treatment * 2nd

-0.053

1.571

-3.13, 3.03

0.973

Pseudo R square

0.001

empower

(Intercept)

19.0

0.570

17.9, 20.2

group

control

—

—

—

treatment

0.559

0.806

-1.02, 2.14

0.489

time_point

1st

—

—

—

2nd

0.160

0.553

-0.925, 1.24

0.774

group * time_point

treatment * 2nd

-0.424

0.790

-1.97, 1.12

0.593

Pseudo R square

0.003

ismi_resistance

(Intercept)

14.5

0.334

13.8, 15.1

group

control

—

—

—

treatment

0.186

0.472

-0.739, 1.11

0.693

time_point

1st

—

—

—

2nd

-0.015

0.460

-0.916, 0.887

0.975

group * time_point

treatment * 2nd

0.473

0.656

-0.813, 1.76

0.473

Pseudo R square

0.008

ismi_discrimation

(Intercept)

12.0

0.415

11.2, 12.8

group

control

—

—

—

treatment

-1.14

0.587

-2.29, 0.016

0.055

time_point

1st

—

—

—

2nd

-0.372

0.463

-1.28, 0.536

0.425

group * time_point

treatment * 2nd

0.400

0.661

-0.894, 1.70

0.547

Pseudo R square

0.026

sss_affective

(Intercept)

10.2

0.453

9.33, 11.1

group

control

—

—

—

treatment

-0.407

0.641

-1.66, 0.849

0.527

time_point

1st

—

—

—

2nd

0.105

0.498

-0.872, 1.08

0.834

group * time_point

treatment * 2nd

-1.16

0.711

-2.55, 0.232

0.107

Pseudo R square

0.021

sss_behavior

(Intercept)

10.1

0.481

9.12, 11.0

group

control

—

—

—

treatment

-0.780

0.681

-2.11, 0.555

0.254

time_point

1st

—

—

—

2nd

-0.067

0.539

-1.12, 0.989

0.901

group * time_point

treatment * 2nd

-0.632

0.769

-2.14, 0.875

0.414

Pseudo R square

0.021

sss_cognitive

(Intercept)

8.34

0.474

7.41, 9.27

group

control

—

—

—

treatment

-0.424

0.670

-1.74, 0.889

0.528

time_point

1st

—

—

—

2nd

0.676

0.523

-0.350, 1.70

0.201

group * time_point

treatment * 2nd

-1.31

0.747

-2.77, 0.158

0.085

Pseudo R square

0.020

sss

(Intercept)

28.6

1.298

26.1, 31.2

group

control

—

—

—

treatment

-1.61

1.836

-5.21, 1.99

0.382

time_point

1st

—

—

—

2nd

0.680

1.323

-1.91, 3.27

0.609

group * time_point

treatment * 2nd

-2.98

1.888

-6.68, 0.719

0.119

Pseudo R square

0.022

1SE = Standard Error, CI = Confidence Interval

Text

recovery_stage_a

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict recovery_stage_a with group and time_point (formula: recovery_stage_a ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.31) and the part related to the fixed effects alone (marginal R2) is of 0.02. The model’s intercept, corresponding to group = control and time_point = 1st, is at 3.29 (95% CI [2.99, 3.59], t(165) = 21.66, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -0.24, 95% CI [-0.66, 0.18], t(165) = -1.11, p = 0.269; Std. beta = -0.20, 95% CI [-0.56, 0.16])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.04, 95% CI [-0.43, 0.51], t(165) = 0.18, p = 0.859; Std. beta = 0.04, 95% CI [-0.37, 0.44])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.51, 95% CI [-0.16, 1.18], t(165) = 1.48, p = 0.138; Std. beta = 0.43, 95% CI [-0.14, 1.01])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

recovery_stage_b

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict recovery_stage_b with group and time_point (formula: recovery_stage_b ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.40) and the part related to the fixed effects alone (marginal R2) is of 6.98e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 17.86 (95% CI [17.15, 18.58], t(165) = 48.94, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.03, 95% CI [-0.98, 1.05], t(165) = 0.07, p = 0.948; Std. beta = 0.01, 95% CI [-0.35, 0.37])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.28, 95% CI [-1.34, 0.78], t(165) = -0.52, p = 0.604; Std. beta = -0.10, 95% CI [-0.48, 0.28])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.79, 95% CI [-0.72, 2.30], t(165) = 1.02, p = 0.307; Std. beta = 0.28, 95% CI [-0.26, 0.82])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

ras_confidence

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict ras_confidence with group and time_point (formula: ras_confidence ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.68) and the part related to the fixed effects alone (marginal R2) is of 0.02. The model’s intercept, corresponding to group = control and time_point = 1st, is at 29.97 (95% CI [28.67, 31.27], t(165) = 45.20, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.36, 95% CI [-1.48, 2.19], t(165) = 0.38, p = 0.704; Std. beta = 0.07, 95% CI [-0.29, 0.43])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.73, 95% CI [-0.75, 2.20], t(165) = 0.96, p = 0.336; Std. beta = 0.14, 95% CI [-0.15, 0.43])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 1.06, 95% CI [-1.05, 3.17], t(165) = 0.99, p = 0.323; Std. beta = 0.21, 95% CI [-0.21, 0.63])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

ras_willingness

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict ras_willingness with group and time_point (formula: ras_willingness ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.69) and the part related to the fixed effects alone (marginal R2) is of 0.02. The model’s intercept, corresponding to group = control and time_point = 1st, is at 11.88 (95% CI [11.36, 12.40], t(165) = 44.90, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.12, 95% CI [-0.61, 0.85], t(165) = 0.32, p = 0.751; Std. beta = 0.06, 95% CI [-0.30, 0.42])
  • The effect of time point [2nd] is statistically significant and negative (beta = -0.64, 95% CI [-1.23, -0.06], t(165) = -2.15, p = 0.032; Std. beta = -0.32, 95% CI [-0.61, -0.03])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.83, 95% CI [-3.81e-03, 1.67], t(165) = 1.95, p = 0.051; Std. beta = 0.41, 95% CI [-1.88e-03, 0.82])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

ras_goal

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict ras_goal with group and time_point (formula: ras_goal ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.64) and the part related to the fixed effects alone (marginal R2) is of 0.02. The model’s intercept, corresponding to group = control and time_point = 1st, is at 17.36 (95% CI [16.54, 18.18], t(165) = 41.46, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.02, 95% CI [-1.14, 1.18], t(165) = 0.03, p = 0.977; Std. beta = 5.27e-03, 95% CI [-0.36, 0.37])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.45, 95% CI [-1.43, 0.54], t(165) = -0.89, p = 0.375; Std. beta = -0.14, 95% CI [-0.44, 0.17])
  • The interaction effect of time point [2nd] on group [treatment] is statistically significant and positive (beta = 1.65, 95% CI [0.25, 3.06], t(165) = 2.31, p = 0.021; Std. beta = 0.51, 95% CI [0.08, 0.95])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

ras_reliance

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict ras_reliance with group and time_point (formula: ras_reliance ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.71) and the part related to the fixed effects alone (marginal R2) is of 0.03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 13.22 (95% CI [12.50, 13.94], t(165) = 35.78, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.24, 95% CI [-0.79, 1.26], t(165) = 0.45, p = 0.650; Std. beta = 0.08, 95% CI [-0.27, 0.44])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.33, 95% CI [-0.47, 1.12], t(165) = 0.81, p = 0.419; Std. beta = 0.11, 95% CI [-0.16, 0.39])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 1.04, 95% CI [-0.09, 2.17], t(165) = 1.81, p = 0.071; Std. beta = 0.36, 95% CI [-0.03, 0.75])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

ras_domination

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict ras_domination with group and time_point (formula: ras_domination ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.46) and the part related to the fixed effects alone (marginal R2) is of 0.03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 10.32 (95% CI [9.74, 10.90], t(165) = 34.73, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -0.61, 95% CI [-1.43, 0.21], t(165) = -1.45, p = 0.147; Std. beta = -0.27, 95% CI [-0.63, 0.09])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.32, 95% CI [-1.15, 0.52], t(165) = -0.74, p = 0.459; Std. beta = -0.14, 95% CI [-0.51, 0.23])
  • The interaction effect of time point [2nd] on group [treatment] is statistically significant and positive (beta = 1.39, 95% CI [0.20, 2.58], t(165) = 2.29, p = 0.022; Std. beta = 0.61, 95% CI [0.09, 1.14])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

symptom

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict symptom with group and time_point (formula: symptom ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.82) and the part related to the fixed effects alone (marginal R2) is of 4.02e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 30.12 (95% CI [27.66, 32.58], t(165) = 24.03, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -0.25, 95% CI [-3.73, 3.22], t(165) = -0.14, p = 0.886; Std. beta = -0.03, 95% CI [-0.39, 0.33])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.15, 95% CI [-2.30, 2.00], t(165) = -0.14, p = 0.890; Std. beta = -0.02, 95% CI [-0.24, 0.21])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -1.40, 95% CI [-4.46, 1.67], t(165) = -0.89, p = 0.372; Std. beta = -0.15, 95% CI [-0.46, 0.17])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

slof_work

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict slof_work with group and time_point (formula: slof_work ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.72) and the part related to the fixed effects alone (marginal R2) is of 4.64e-04. The model’s intercept, corresponding to group = control and time_point = 1st, is at 22.42 (95% CI [21.21, 23.63], t(165) = 36.31, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -0.24, 95% CI [-1.95, 1.47], t(165) = -0.27, p = 0.786; Std. beta = -0.05, 95% CI [-0.41, 0.31])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.19, 95% CI [-1.48, 1.10], t(165) = -0.29, p = 0.771; Std. beta = -0.04, 95% CI [-0.31, 0.23])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.30, 95% CI [-1.53, 2.14], t(165) = 0.32, p = 0.746; Std. beta = 0.06, 95% CI [-0.33, 0.45])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

slof_relationship

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict slof_relationship with group and time_point (formula: slof_relationship ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.75) and the part related to the fixed effects alone (marginal R2) is of 0.02. The model’s intercept, corresponding to group = control and time_point = 1st, is at 24.95 (95% CI [23.45, 26.45], t(165) = 32.66, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.92, 95% CI [-1.20, 3.03], t(165) = 0.85, p = 0.397; Std. beta = 0.16, 95% CI [-0.21, 0.52])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -1.15, 95% CI [-2.67, 0.37], t(165) = -1.49, p = 0.137; Std. beta = -0.20, 95% CI [-0.46, 0.06])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 1.85, 95% CI [-0.32, 4.01], t(165) = 1.67, p = 0.095; Std. beta = 0.32, 95% CI [-0.05, 0.69])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

satisfaction

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict satisfaction with group and time_point (formula: satisfaction ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.66) and the part related to the fixed effects alone (marginal R2) is of 0.02. The model’s intercept, corresponding to group = control and time_point = 1st, is at 19.76 (95% CI [17.96, 21.57], t(165) = 21.45, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 1.64, 95% CI [-0.91, 4.20], t(165) = 1.26, p = 0.207; Std. beta = 0.23, 95% CI [-0.13, 0.59])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.67, 95% CI [-1.43, 2.77], t(165) = 0.62, p = 0.534; Std. beta = 0.09, 95% CI [-0.20, 0.39])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.41, 95% CI [-2.59, 3.41], t(165) = 0.27, p = 0.789; Std. beta = 0.06, 95% CI [-0.37, 0.48])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

mhc_emotional

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict mhc_emotional with group and time_point (formula: mhc_emotional ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.75) and the part related to the fixed effects alone (marginal R2) is of 5.45e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 10.81 (95% CI [9.84, 11.79], t(165) = 21.75, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.58, 95% CI [-0.80, 1.95], t(165) = 0.82, p = 0.412; Std. beta = 0.15, 95% CI [-0.21, 0.52])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.35, 95% CI [-0.64, 1.35], t(165) = 0.70, p = 0.485; Std. beta = 0.09, 95% CI [-0.17, 0.36])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.22, 95% CI [-1.64, 1.20], t(165) = -0.30, p = 0.761; Std. beta = -0.06, 95% CI [-0.43, 0.32])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

mhc_social

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict mhc_social with group and time_point (formula: mhc_social ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.65) and the part related to the fixed effects alone (marginal R2) is of 1.69e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 15.20 (95% CI [13.74, 16.67], t(165) = 20.38, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -0.10, 95% CI [-2.17, 1.97], t(165) = -0.10, p = 0.923; Std. beta = -0.02, 95% CI [-0.38, 0.35])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.57, 95% CI [-1.15, 2.29], t(165) = 0.65, p = 0.515; Std. beta = 0.10, 95% CI [-0.20, 0.41])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.23, 95% CI [-2.69, 2.22], t(165) = -0.19, p = 0.853; Std. beta = -0.04, 95% CI [-0.48, 0.39])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

mhc_psychological

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict mhc_psychological with group and time_point (formula: mhc_psychological ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.67) and the part related to the fixed effects alone (marginal R2) is of 3.78e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 21.69 (95% CI [19.99, 23.40], t(165) = 24.97, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.53, 95% CI [-1.88, 2.93], t(165) = 0.43, p = 0.669; Std. beta = 0.08, 95% CI [-0.28, 0.44])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.73, 95% CI [-1.21, 2.68], t(165) = 0.74, p = 0.460; Std. beta = 0.11, 95% CI [-0.18, 0.40])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.06, 95% CI [-2.84, 2.71], t(165) = -0.04, p = 0.965; Std. beta = -9.43e-03, 95% CI [-0.43, 0.41])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

resilisnce

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict resilisnce with group and time_point (formula: resilisnce ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.64) and the part related to the fixed effects alone (marginal R2) is of 0.03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 16.20 (95% CI [15.04, 17.36], t(165) = 27.36, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.93, 95% CI [-0.71, 2.57], t(165) = 1.11, p = 0.266; Std. beta = 0.21, 95% CI [-0.16, 0.57])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.16, 95% CI [-1.24, 1.56], t(165) = 0.22, p = 0.825; Std. beta = 0.03, 95% CI [-0.27, 0.34])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 1.42, 95% CI [-0.57, 3.42], t(165) = 1.40, p = 0.162; Std. beta = 0.31, 95% CI [-0.13, 0.75])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

social_provision

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict social_provision with group and time_point (formula: social_provision ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.61) and the part related to the fixed effects alone (marginal R2) is of 0.03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 13.36 (95% CI [12.62, 14.09], t(165) = 35.75, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.75, 95% CI [-0.29, 1.78], t(165) = 1.41, p = 0.158; Std. beta = 0.25, 95% CI [-0.10, 0.61])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.62, 95% CI [-1.54, 0.30], t(165) = -1.31, p = 0.189; Std. beta = -0.21, 95% CI [-0.53, 0.10])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.76, 95% CI [-0.55, 2.07], t(165) = 1.13, p = 0.256; Std. beta = 0.26, 95% CI [-0.19, 0.71])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

els_value_living

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict els_value_living with group and time_point (formula: els_value_living ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.65) and the part related to the fixed effects alone (marginal R2) is of 0.02. The model’s intercept, corresponding to group = control and time_point = 1st, is at 16.68 (95% CI [15.88, 17.48], t(165) = 40.99, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.68, 95% CI [-0.45, 1.81], t(165) = 1.18, p = 0.239; Std. beta = 0.22, 95% CI [-0.14, 0.58])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.23, 95% CI [-0.71, 1.18], t(165) = 0.48, p = 0.628; Std. beta = 0.07, 95% CI [-0.23, 0.38])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.29, 95% CI [-1.06, 1.65], t(165) = 0.42, p = 0.671; Std. beta = 0.09, 95% CI [-0.34, 0.52])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

els_life_fulfill

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict els_life_fulfill with group and time_point (formula: els_life_fulfill ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.79) and the part related to the fixed effects alone (marginal R2) is of 0.03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 12.19 (95% CI [11.34, 13.03], t(165) = 28.19, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 1.10, 95% CI [-0.10, 2.30], t(165) = 1.80, p = 0.072; Std. beta = 0.33, 95% CI [-0.03, 0.70])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.58, 95% CI [-0.22, 1.39], t(165) = 1.41, p = 0.158; Std. beta = 0.18, 95% CI [-0.07, 0.42])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.26, 95% CI [-1.41, 0.89], t(165) = -0.44, p = 0.661; Std. beta = -0.08, 95% CI [-0.43, 0.27])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

els

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict els with group and time_point (formula: els ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.78) and the part related to the fixed effects alone (marginal R2) is of 0.03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 28.86 (95% CI [27.35, 30.38], t(165) = 37.35, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 1.78, 95% CI [-0.36, 3.92], t(165) = 1.63, p = 0.103; Std. beta = 0.30, 95% CI [-0.06, 0.66])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.79, 95% CI [-0.68, 2.27], t(165) = 1.06, p = 0.290; Std. beta = 0.13, 95% CI [-0.11, 0.38])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.04, 95% CI [-2.06, 2.14], t(165) = 0.04, p = 0.971; Std. beta = 6.49e-03, 95% CI [-0.35, 0.36])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

social_connect

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict social_connect with group and time_point (formula: social_connect ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.76) and the part related to the fixed effects alone (marginal R2) is of 0.03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 27.14 (95% CI [24.74, 29.53], t(165) = 22.22, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -1.44, 95% CI [-4.83, 1.94], t(165) = -0.83, p = 0.404; Std. beta = -0.15, 95% CI [-0.51, 0.20])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 1.22, 95% CI [-1.17, 3.60], t(165) = 1.00, p = 0.317; Std. beta = 0.13, 95% CI [-0.12, 0.38])
  • The interaction effect of time point [2nd] on group [treatment] is statistically significant and negative (beta = -3.62, 95% CI [-7.03, -0.22], t(165) = -2.09, p = 0.037; Std. beta = -0.38, 95% CI [-0.74, -0.02])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

shs_agency

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict shs_agency with group and time_point (formula: shs_agency ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.74) and the part related to the fixed effects alone (marginal R2) is of 0.01. The model’s intercept, corresponding to group = control and time_point = 1st, is at 14.05 (95% CI [12.75, 15.35], t(165) = 21.13, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.69, 95% CI [-1.15, 2.54], t(165) = 0.74, p = 0.460; Std. beta = 0.14, 95% CI [-0.23, 0.51])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.06, 95% CI [-1.28, 1.40], t(165) = 0.08, p = 0.933; Std. beta = 0.01, 95% CI [-0.26, 0.28])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.82, 95% CI [-1.09, 2.74], t(165) = 0.84, p = 0.398; Std. beta = 0.16, 95% CI [-0.22, 0.55])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

shs_pathway

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict shs_pathway with group and time_point (formula: shs_pathway ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.74) and the part related to the fixed effects alone (marginal R2) is of 2.96e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 16.10 (95% CI [15.09, 17.11], t(165) = 31.17, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.41, 95% CI [-1.02, 1.84], t(165) = 0.56, p = 0.578; Std. beta = 0.10, 95% CI [-0.26, 0.47])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.10, 95% CI [-0.93, 1.14], t(165) = 0.20, p = 0.844; Std. beta = 0.03, 95% CI [-0.24, 0.29])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.03, 95% CI [-1.44, 1.51], t(165) = 0.04, p = 0.964; Std. beta = 8.61e-03, 95% CI [-0.37, 0.39])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

shs

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict shs with group and time_point (formula: shs ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.76) and the part related to the fixed effects alone (marginal R2) is of 7.57e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 30.15 (95% CI [27.94, 32.36], t(165) = 26.76, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 1.10, 95% CI [-2.02, 4.23], t(165) = 0.69, p = 0.489; Std. beta = 0.13, 95% CI [-0.24, 0.50])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.17, 95% CI [-2.00, 2.35], t(165) = 0.15, p = 0.878; Std. beta = 0.02, 95% CI [-0.24, 0.28])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.83, 95% CI [-2.27, 3.94], t(165) = 0.53, p = 0.599; Std. beta = 0.10, 95% CI [-0.27, 0.46])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

esteem

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict esteem with group and time_point (formula: esteem ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.36) and the part related to the fixed effects alone (marginal R2) is of 6.33e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 12.75 (95% CI [12.35, 13.14], t(165) = 62.88, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -0.27, 95% CI [-0.83, 0.29], t(165) = -0.95, p = 0.344; Std. beta = -0.18, 95% CI [-0.55, 0.19])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.01, 95% CI [-0.62, 0.59], t(165) = -0.05, p = 0.963; Std. beta = -9.37e-03, 95% CI [-0.41, 0.39])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.25, 95% CI [-0.62, 1.12], t(165) = 0.57, p = 0.571; Std. beta = 0.16, 95% CI [-0.40, 0.73])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

mlq_search

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict mlq_search with group and time_point (formula: mlq_search ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.55) and the part related to the fixed effects alone (marginal R2) is of 5.07e-04. The model’s intercept, corresponding to group = control and time_point = 1st, is at 14.71 (95% CI [13.81, 15.61], t(165) = 32.05, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.17, 95% CI [-1.10, 1.44], t(165) = 0.26, p = 0.794; Std. beta = 0.05, 95% CI [-0.32, 0.41])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.16, 95% CI [-1.03, 1.34], t(165) = 0.26, p = 0.794; Std. beta = 0.05, 95% CI [-0.29, 0.38])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.16, 95% CI [-1.85, 1.53], t(165) = -0.18, p = 0.854; Std. beta = -0.05, 95% CI [-0.53, 0.44])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

mlq_presence

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict mlq_presence with group and time_point (formula: mlq_presence ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.66) and the part related to the fixed effects alone (marginal R2) is of 1.47e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 13.34 (95% CI [12.26, 14.42], t(165) = 24.15, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.12, 95% CI [-1.41, 1.65], t(165) = 0.15, p = 0.879; Std. beta = 0.03, 95% CI [-0.34, 0.39])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.26, 95% CI [-0.99, 1.51], t(165) = 0.41, p = 0.685; Std. beta = 0.06, 95% CI [-0.24, 0.36])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.10, 95% CI [-1.69, 1.89], t(165) = 0.11, p = 0.913; Std. beta = 0.02, 95% CI [-0.40, 0.45])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

mlq

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict mlq with group and time_point (formula: mlq ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.63) and the part related to the fixed effects alone (marginal R2) is of 1.08e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 28.05 (95% CI [26.27, 29.84], t(165) = 30.80, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.29, 95% CI [-2.24, 2.81], t(165) = 0.22, p = 0.823; Std. beta = 0.04, 95% CI [-0.32, 0.40])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.43, 95% CI [-1.73, 2.59], t(165) = 0.39, p = 0.698; Std. beta = 0.06, 95% CI [-0.25, 0.37])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.05, 95% CI [-3.13, 3.03], t(165) = -0.03, p = 0.973; Std. beta = -7.63e-03, 95% CI [-0.45, 0.44])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

empower

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict empower with group and time_point (formula: empower ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.77) and the part related to the fixed effects alone (marginal R2) is of 2.93e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 19.03 (95% CI [17.92, 20.15], t(165) = 33.38, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.56, 95% CI [-1.02, 2.14], t(165) = 0.69, p = 0.488; Std. beta = 0.13, 95% CI [-0.24, 0.49])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.16, 95% CI [-0.92, 1.24], t(165) = 0.29, p = 0.773; Std. beta = 0.04, 95% CI [-0.21, 0.29])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.42, 95% CI [-1.97, 1.12], t(165) = -0.54, p = 0.591; Std. beta = -0.10, 95% CI [-0.46, 0.26])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

ismi_resistance

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict ismi_resistance with group and time_point (formula: ismi_resistance ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.50) and the part related to the fixed effects alone (marginal R2) is of 7.54e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 14.47 (95% CI [13.82, 15.13], t(165) = 43.37, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.19, 95% CI [-0.74, 1.11], t(165) = 0.40, p = 0.693; Std. beta = 0.07, 95% CI [-0.29, 0.43])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.01, 95% CI [-0.92, 0.89], t(165) = -0.03, p = 0.975; Std. beta = -5.73e-03, 95% CI [-0.36, 0.35])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.47, 95% CI [-0.81, 1.76], t(165) = 0.72, p = 0.471; Std. beta = 0.18, 95% CI [-0.32, 0.69])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

ismi_discrimation

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict ismi_discrimation with group and time_point (formula: ismi_discrimation ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.70) and the part related to the fixed effects alone (marginal R2) is of 0.03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 12.02 (95% CI [11.20, 12.83], t(165) = 28.94, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -1.14, 95% CI [-2.29, 0.02], t(165) = -1.93, p = 0.053; Std. beta = -0.35, 95% CI [-0.71, 4.81e-03])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.37, 95% CI [-1.28, 0.54], t(165) = -0.80, p = 0.422; Std. beta = -0.11, 95% CI [-0.40, 0.17])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.40, 95% CI [-0.89, 1.70], t(165) = 0.61, p = 0.544; Std. beta = 0.12, 95% CI [-0.28, 0.52])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

sss_affective

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict sss_affective with group and time_point (formula: sss_affective ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.71) and the part related to the fixed effects alone (marginal R2) is of 0.02. The model’s intercept, corresponding to group = control and time_point = 1st, is at 10.22 (95% CI [9.33, 11.11], t(165) = 22.56, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -0.41, 95% CI [-1.66, 0.85], t(165) = -0.63, p = 0.525; Std. beta = -0.11, 95% CI [-0.47, 0.24])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.10, 95% CI [-0.87, 1.08], t(165) = 0.21, p = 0.834; Std. beta = 0.03, 95% CI [-0.24, 0.30])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -1.16, 95% CI [-2.55, 0.23], t(165) = -1.63, p = 0.102; Std. beta = -0.32, 95% CI [-0.71, 0.06])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

sss_behavior

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict sss_behavior with group and time_point (formula: sss_behavior ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.69) and the part related to the fixed effects alone (marginal R2) is of 0.02. The model’s intercept, corresponding to group = control and time_point = 1st, is at 10.07 (95% CI [9.12, 11.01], t(165) = 20.91, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -0.78, 95% CI [-2.11, 0.55], t(165) = -1.15, p = 0.252; Std. beta = -0.21, 95% CI [-0.56, 0.15])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.07, 95% CI [-1.12, 0.99], t(165) = -0.12, p = 0.901; Std. beta = -0.02, 95% CI [-0.30, 0.26])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.63, 95% CI [-2.14, 0.88], t(165) = -0.82, p = 0.411; Std. beta = -0.17, 95% CI [-0.57, 0.23])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

sss_cognitive

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict sss_cognitive with group and time_point (formula: sss_cognitive ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.70) and the part related to the fixed effects alone (marginal R2) is of 0.02. The model’s intercept, corresponding to group = control and time_point = 1st, is at 8.34 (95% CI [7.41, 9.27], t(165) = 17.60, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -0.42, 95% CI [-1.74, 0.89], t(165) = -0.63, p = 0.527; Std. beta = -0.11, 95% CI [-0.47, 0.24])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.68, 95% CI [-0.35, 1.70], t(165) = 1.29, p = 0.196; Std. beta = 0.18, 95% CI [-0.09, 0.46])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -1.31, 95% CI [-2.77, 0.16], t(165) = -1.75, p = 0.080; Std. beta = -0.35, 95% CI [-0.75, 0.04])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

sss

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict sss with group and time_point (formula: sss ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.75) and the part related to the fixed effects alone (marginal R2) is of 0.02. The model’s intercept, corresponding to group = control and time_point = 1st, is at 28.63 (95% CI [26.08, 31.17], t(165) = 22.05, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -1.61, 95% CI [-5.21, 1.99], t(165) = -0.88, p = 0.381; Std. beta = -0.16, 95% CI [-0.51, 0.19])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.68, 95% CI [-1.91, 3.27], t(165) = 0.51, p = 0.607; Std. beta = 0.07, 95% CI [-0.19, 0.32])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -2.98, 95% CI [-6.68, 0.72], t(165) = -1.58, p = 0.114; Std. beta = -0.29, 95% CI [-0.65, 0.07])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

Likelihood ratio tests

outcome

model

npar

AIC

BIC

logLik

deviance

Chisq

Df

p

recovery_stage_a

null

3

540.523

549.948

-267.261

534.523

recovery_stage_a

random

6

541.094

559.944

-264.547

529.094

5.429

3

0.143

recovery_stage_b

null

3

832.118

841.543

-413.059

826.118

recovery_stage_b

random

6

836.703

855.553

-412.351

824.703

1.415

3

0.702

ras_confidence

null

3

1,018.452

1,027.877

-506.226

1,012.452

ras_confidence

random

6

1,017.715

1,036.565

-502.857

1,005.715

6.737

3

0.081

ras_willingness

null

3

702.673

712.098

-348.337

696.673

ras_willingness

random

6

702.925

721.775

-345.463

690.925

5.748

3

0.125

ras_goal

null

3

866.189

875.614

-430.095

860.189

ras_goal

random

6

865.369

884.219

-426.685

853.369

6.820

3

0.078

ras_reliance

null

3

820.178

829.603

-407.089

814.178

ras_reliance

random

6

814.063

832.913

-401.032

802.063

12.115

3

0.007

ras_domination

null

3

764.491

773.916

-379.246

758.491

ras_domination

random

6

763.660

782.510

-375.830

751.660

6.831

3

0.077

symptom

null

3

1,205.739

1,215.164

-599.869

1,199.739

symptom

random

6

1,209.658

1,228.508

-598.829

1,197.658

2.081

3

0.556

slof_work

null

3

981.129

990.554

-487.564

975.129

slof_work

random

6

986.973

1,005.823

-487.487

974.973

0.156

3

0.984

slof_relationship

null

3

1,053.707

1,063.132

-523.854

1,047.707

slof_relationship

random

6

1,055.019

1,073.869

-521.510

1,043.019

4.688

3

0.196

satisfaction

null

3

1,129.702

1,139.127

-561.851

1,123.702

satisfaction

random

6

1,132.358

1,151.208

-560.179

1,120.358

3.344

3

0.342

mhc_emotional

null

3

903.753

913.178

-448.876

897.753

mhc_emotional

random

6

908.590

927.440

-448.295

896.590

1.163

3

0.762

mhc_social

null

3

1,055.820

1,065.245

-524.910

1,049.820

mhc_social

random

6

1,061.209

1,080.059

-524.604

1,049.209

0.611

3

0.894

mhc_psychological

null

3

1,105.693

1,115.118

-549.847

1,099.693

mhc_psychological

random

6

1,110.496

1,129.346

-549.248

1,098.496

1.197

3

0.754

resilisnce

null

3

985.850

995.275

-489.925

979.850

resilisnce

random

6

984.591

1,003.441

-486.295

972.591

7.259

3

0.064

social_provision

null

3

830.134

839.559

-412.067

824.134

social_provision

random

6

830.753

849.603

-409.377

818.753

5.380

3

0.146

els_value_living

null

3

852.078

861.503

-423.039

846.078

els_value_living

random

6

854.800

873.650

-421.400

842.800

3.278

3

0.351

els_life_fulfill

null

3

853.579

863.004

-423.789

847.579

els_life_fulfill

random

6

853.906

872.756

-420.953

841.906

5.673

3

0.129

els

null

3

1,053.965

1,063.389

-523.982

1,047.965

els

random

6

1,054.798

1,073.648

-521.399

1,042.798

5.167

3

0.160

social_connect

null

3

1,214.433

1,223.858

-604.216

1,208.433

social_connect

random

6

1,213.780

1,232.630

-600.890

1,201.780

6.653

3

0.084

shs_agency

null

3

1,005.619

1,015.044

-499.809

999.619

shs_agency

random

6

1,009.002

1,027.852

-498.501

997.002

2.617

3

0.455

shs_pathway

null

3

916.531

925.956

-455.265

910.531

shs_pathway

random

6

922.080

940.930

-455.040

910.080

0.451

3

0.930

shs

null

3

1,180.643

1,190.068

-587.321

1,174.643

shs

random

6

1,185.101

1,203.951

-586.551

1,173.101

1.542

3

0.673

esteem

null

3

632.903

642.328

-313.452

626.903

esteem

random

6

637.698

656.548

-312.849

625.698

1.205

3

0.752

mlq_search

null

3

899.404

908.829

-446.702

893.404

mlq_search

random

6

905.289

924.139

-446.645

893.289

0.115

3

0.990

mlq_presence

null

3

951.332

960.757

-472.666

945.332

mlq_presence

random

6

956.813

975.663

-472.406

944.813

0.519

3

0.915

mlq

null

3

1,126.254

1,135.679

-560.127

1,120.254

mlq

random

6

1,131.933

1,150.783

-559.966

1,119.933

0.321

3

0.956

empower

null

3

945.342

954.767

-469.671

939.342

empower

random

6

950.682

969.532

-469.341

938.682

0.660

3

0.883

ismi_resistance

null

3

795.645

805.070

-394.822

789.645

ismi_resistance

random

6

800.164

819.014

-394.082

788.164

1.481

3

0.687

ismi_discrimation

null

3

853.817

863.242

-423.909

847.817

ismi_discrimation

random

6

855.770

874.620

-421.885

843.770

4.047

3

0.256

sss_affective

null

3

883.820

893.245

-438.910

877.820

sss_affective

random

6

884.147

902.996

-436.073

872.147

5.674

3

0.129

sss_behavior

null

3

904.378

913.803

-449.189

898.378

sss_behavior

random

6

906.683

925.533

-447.342

894.683

3.695

3

0.296

sss_cognitive

null

3

898.378

907.803

-446.189

892.378

sss_cognitive

random

6

899.927

918.777

-443.963

887.927

4.451

3

0.217

sss

null

3

1,235.860

1,245.285

-614.930

1,229.860

sss

random

6

1,236.923

1,255.773

-612.462

1,224.923

4.937

3

0.176

Post hoc analysis

Table

outcome

time

control

treatment

between

n

estimate

within es

n

estimate

within es

p

es

recovery_stage_a

1st

59

3.29 ± 1.17

59

3.05 ± 1.17

0.271

0.241

recovery_stage_a

2nd

27

3.33 ± 1.15

-0.044

26

3.60 ± 1.15

-0.561

0.392

-0.276

recovery_stage_b

1st

59

17.86 ± 2.80

59

17.90 ± 2.80

0.948

-0.016

recovery_stage_b

2nd

27

17.58 ± 2.70

0.129

26

18.41 ± 2.70

-0.233

0.269

-0.378

ras_confidence

1st

59

29.97 ± 5.09

59

30.32 ± 5.09

0.705

-0.123

ras_confidence

2nd

27

30.69 ± 4.43

-0.250

26

32.11 ± 4.41

-0.616

0.245

-0.489

ras_willingness

1st

59

11.88 ± 2.03

59

12.00 ± 2.03

0.752

-0.103

ras_willingness

2nd

27

11.24 ± 1.77

0.559

26

12.19 ± 1.76

-0.165

0.051

-0.827

ras_goal

1st

59

17.36 ± 3.22

59

17.37 ± 3.22

0.977

-0.009

ras_goal

2nd

27

16.91 ± 2.85

0.229

26

18.58 ± 2.84

-0.621

0.034

-0.859

ras_reliance

1st

59

13.22 ± 2.84

59

13.46 ± 2.84

0.650

-0.153

ras_reliance

2nd

27

13.55 ± 2.44

-0.211

26

14.83 ± 2.42

-0.884

0.057

-0.826

ras_domination

1st

59

10.32 ± 2.28

59

9.71 ± 2.28

0.149

0.360

ras_domination

2nd

27

10.01 ± 2.17

0.186

26

10.79 ± 2.17

-0.634

0.192

-0.460

symptom

1st

59

30.12 ± 9.63

59

29.86 ± 9.63

0.886

0.062

symptom

2nd

27

29.97 ± 7.71

0.037

26

28.32 ± 7.64

0.375

0.434

0.400

slof_work

1st

59

22.42 ± 4.74

59

22.19 ± 4.74

0.786

0.094

slof_work

2nd

27

22.23 ± 4.03

0.076

26

22.30 ± 4.01

-0.045

0.952

-0.026

slof_relationship

1st

59

24.95 ± 5.87

59

25.86 ± 5.87

0.398

-0.310

slof_relationship

2nd

27

23.80 ± 4.91

0.390

26

26.56 ± 4.88

-0.236

0.041

-0.937

satisfaction

1st

59

19.76 ± 7.08

59

21.41 ± 7.08

0.209

-0.397

satisfaction

2nd

27

20.43 ± 6.21

-0.161

26

22.49 ± 6.18

-0.261

0.229

-0.496

mhc_emotional

1st

59

10.81 ± 3.82

59

11.39 ± 3.82

0.414

-0.299

mhc_emotional

2nd

27

11.17 ± 3.20

-0.183

26

11.52 ± 3.18

-0.069

0.685

-0.185

mhc_social

1st

59

15.20 ± 5.73

59

15.10 ± 5.73

0.923

0.030

mhc_social

2nd

27

15.77 ± 5.05

-0.168

26

15.44 ± 5.03

-0.100

0.810

0.098

mhc_psychological

1st

59

21.69 ± 6.67

59

22.22 ± 6.67

0.670

-0.138

mhc_psychological

2nd

27

22.43 ± 5.82

-0.192

26

22.89 ± 5.79

-0.175

0.772

-0.121

resilisnce

1st

59

16.20 ± 4.55

59

17.14 ± 4.55

0.268

-0.337

resilisnce

2nd

27

16.36 ± 4.05

-0.057

26

18.72 ± 4.03

-0.571

0.035

-0.851

social_provision

1st

59

13.36 ± 2.87

59

14.10 ± 2.87

0.160

-0.407

social_provision

2nd

27

12.74 ± 2.59

0.337

26

14.25 ± 2.58

-0.079

0.036

-0.823

els_value_living

1st

59

16.68 ± 3.13

59

17.36 ± 3.13

0.241

-0.362

els_value_living

2nd

27

16.91 ± 2.77

-0.125

26

17.88 ± 2.75

-0.282

0.202

-0.519

els_life_fulfill

1st

59

12.19 ± 3.32

59

13.29 ± 3.32

0.074

-0.708

els_life_fulfill

2nd

27

12.77 ± 2.72

-0.373

26

13.61 ± 2.70

-0.208

0.259

-0.543

els

1st

59

28.86 ± 5.94

59

30.64 ± 5.94

0.106

-0.625

els

2nd

27

29.66 ± 4.90

-0.279

26

31.48 ± 4.87

-0.292

0.177

-0.638

social_connect

1st

59

27.14 ± 9.38

59

25.69 ± 9.38

0.406

0.311

social_connect

2nd

27

28.35 ± 7.81

-0.263

26

23.29 ± 7.75

0.520

0.019

1.095

shs_agency

1st

59

14.05 ± 5.11

59

14.75 ± 5.11

0.461

-0.267

shs_agency

2nd

27

14.11 ± 4.29

-0.022

26

15.63 ± 4.27

-0.338

0.198

-0.583

shs_pathway

1st

59

16.10 ± 3.97

59

16.51 ± 3.97

0.579

-0.202

shs_pathway

2nd

27

16.21 ± 3.33

-0.052

26

16.65 ± 3.31

-0.068

0.630

-0.219

shs

1st

59

30.15 ± 8.66

59

31.25 ± 8.66

0.491

-0.261

shs

2nd

27

30.32 ± 7.18

-0.040

26

32.26 ± 7.13

-0.238

0.326

-0.459

esteem

1st

59

12.75 ± 1.56

59

12.47 ± 1.56

0.346

0.216

esteem

2nd

27

12.73 ± 1.52

0.011

26

12.71 ± 1.52

-0.188

0.960

0.017

mlq_search

1st

59

14.71 ± 3.53

59

14.88 ± 3.53

0.794

-0.071

mlq_search

2nd

27

14.87 ± 3.24

-0.066

26

14.88 ± 3.23

0.000

0.990

-0.004

mlq_presence

1st

59

13.34 ± 4.24

59

13.46 ± 4.24

0.879

-0.048

mlq_presence

2nd

27

13.60 ± 3.72

-0.105

26

13.82 ± 3.70

-0.146

0.831

-0.088

mlq

1st

59

28.05 ± 7.00

59

28.34 ± 7.00

0.823

-0.068

mlq

2nd

27

28.48 ± 6.23

-0.100

26

28.71 ± 6.20

-0.088

0.891

-0.055

empower

1st

59

19.03 ± 4.38

59

19.59 ± 4.38

0.489

-0.266

empower

2nd

27

19.19 ± 3.61

-0.076

26

19.33 ± 3.59

0.126

0.891

-0.064

ismi_resistance

1st

59

14.47 ± 2.56

59

14.66 ± 2.56

0.693

-0.103

ismi_resistance

2nd

27

14.46 ± 2.40

0.008

26

15.12 ± 2.40

-0.252

0.319

-0.363

ismi_discrimation

1st

59

12.02 ± 3.19

59

10.88 ± 3.19

0.055

0.639

ismi_discrimation

2nd

27

11.65 ± 2.76

0.209

26

10.91 ± 2.74

-0.016

0.332

0.414

sss_affective

1st

59

10.22 ± 3.48

59

9.81 ± 3.48

0.527

0.213

sss_affective

2nd

27

10.32 ± 2.99

-0.055

26

8.76 ± 2.98

0.553

0.058

0.821

sss_behavior

1st

59

10.07 ± 3.70

59

9.29 ± 3.70

0.254

0.377

sss_behavior

2nd

27

10.00 ± 3.20

0.032

26

8.59 ± 3.18

0.338

0.110

0.682

sss_cognitive

1st

59

8.34 ± 3.64

59

7.92 ± 3.64

0.528

0.211

sss_cognitive

2nd

27

9.02 ± 3.14

-0.337

26

7.29 ± 3.12

0.314

0.046

0.862

sss

1st

59

28.63 ± 9.97

59

27.02 ± 9.97

0.382

0.320

sss

2nd

27

29.31 ± 8.36

-0.135

26

24.72 ± 8.30

0.457

0.047

0.911

Between group

recovery_stage_a

1st

t(159.10) = -1.11, p = 0.271, Cohen d = 0.24, 95% CI (-0.66 to 0.19)

2st

t(162.66) = 0.86, p = 0.392, Cohen d = -0.28, 95% CI (-0.35 to 0.89)

recovery_stage_b

1st

t(153.04) = 0.07, p = 0.948, Cohen d = -0.02, 95% CI (-0.99 to 1.05)

2st

t(160.55) = 1.11, p = 0.269, Cohen d = -0.38, 95% CI (-0.64 to 2.29)

ras_confidence

1st

t(135.08) = 0.38, p = 0.705, Cohen d = -0.12, 95% CI (-1.50 to 2.21)

2st

t(163.25) = 1.17, p = 0.245, Cohen d = -0.49, 95% CI (-0.98 to 3.82)

ras_willingness

1st

t(134.77) = 0.32, p = 0.752, Cohen d = -0.10, 95% CI (-0.62 to 0.86)

2st

t(163.43) = 1.97, p = 0.051, Cohen d = -0.83, 95% CI (-0.00 to 1.91)

ras_goal

1st

t(137.71) = 0.03, p = 0.977, Cohen d = -0.01, 95% CI (-1.15 to 1.19)

2st

t(161.90) = 2.13, p = 0.034, Cohen d = -0.86, 95% CI (0.12 to 3.22)

ras_reliance

1st

t(133.36) = 0.45, p = 0.650, Cohen d = -0.15, 95% CI (-0.80 to 1.27)

2st

t(164.25) = 1.92, p = 0.057, Cohen d = -0.83, 95% CI (-0.04 to 2.60)

ras_domination

1st

t(149.98) = -1.45, p = 0.149, Cohen d = 0.36, 95% CI (-1.44 to 0.22)

2st

t(159.98) = 1.31, p = 0.192, Cohen d = -0.46, 95% CI (-0.40 to 1.96)

symptom

1st

t(126.24) = -0.14, p = 0.886, Cohen d = 0.06, 95% CI (-3.76 to 3.25)

2st

t(166.88) = -0.78, p = 0.434, Cohen d = 0.40, 95% CI (-5.81 to 2.51)

slof_work

1st

t(132.19) = -0.27, p = 0.786, Cohen d = 0.09, 95% CI (-1.96 to 1.49)

2st

t(164.96) = 0.06, p = 0.952, Cohen d = -0.03, 95% CI (-2.12 to 2.25)

slof_relationship

1st

t(130.45) = 0.85, p = 0.398, Cohen d = -0.31, 95% CI (-1.22 to 3.05)

2st

t(165.94) = 2.05, p = 0.041, Cohen d = -0.94, 95% CI (0.11 to 5.42)

satisfaction

1st

t(136.19) = 1.26, p = 0.209, Cohen d = -0.40, 95% CI (-0.93 to 4.22)

2st

t(162.65) = 1.21, p = 0.229, Cohen d = -0.50, 95% CI (-1.31 to 5.42)

mhc_emotional

1st

t(130.59) = 0.82, p = 0.414, Cohen d = -0.30, 95% CI (-0.81 to 1.97)

2st

t(165.87) = 0.41, p = 0.685, Cohen d = -0.18, 95% CI (-1.37 to 2.09)

mhc_social

1st

t(136.72) = -0.10, p = 0.923, Cohen d = 0.03, 95% CI (-2.19 to 1.98)

2st

t(162.37) = -0.24, p = 0.810, Cohen d = 0.10, 95% CI (-3.07 to 2.40)

mhc_psychological

1st

t(135.22) = 0.43, p = 0.670, Cohen d = -0.14, 95% CI (-1.90 to 2.96)

2st

t(163.18) = 0.29, p = 0.772, Cohen d = -0.12, 95% CI (-2.69 to 3.61)

resilisnce

1st

t(138.05) = 1.11, p = 0.268, Cohen d = -0.34, 95% CI (-0.72 to 2.59)

2st

t(161.75) = 2.12, p = 0.035, Cohen d = -0.85, 95% CI (0.16 to 4.55)

social_provision

1st

t(140.46) = 1.41, p = 0.160, Cohen d = -0.41, 95% CI (-0.30 to 1.79)

2st

t(160.82) = 2.12, p = 0.036, Cohen d = -0.82, 95% CI (0.10 to 2.91)

els_value_living

1st

t(137.24) = 1.18, p = 0.241, Cohen d = -0.36, 95% CI (-0.46 to 1.82)

2st

t(162.12) = 1.28, p = 0.202, Cohen d = -0.52, 95% CI (-0.53 to 2.47)

els_life_fulfill

1st

t(128.41) = 1.80, p = 0.074, Cohen d = -0.71, 95% CI (-0.11 to 2.31)

2st

t(166.80) = 1.13, p = 0.259, Cohen d = -0.54, 95% CI (-0.63 to 2.32)

els

1st

t(129.06) = 1.63, p = 0.106, Cohen d = -0.62, 95% CI (-0.38 to 3.94)

2st

t(166.59) = 1.36, p = 0.177, Cohen d = -0.64, 95% CI (-0.83 to 4.47)

social_connect

1st

t(129.87) = -0.83, p = 0.406, Cohen d = 0.31, 95% CI (-4.86 to 1.98)

2st

t(166.24) = -2.37, p = 0.019, Cohen d = 1.09, 95% CI (-9.28 to -0.84)

shs_agency

1st

t(130.94) = 0.74, p = 0.461, Cohen d = -0.27, 95% CI (-1.17 to 2.56)

2st

t(165.68) = 1.29, p = 0.198, Cohen d = -0.58, 95% CI (-0.80 to 3.84)

shs_pathway

1st

t(130.76) = 0.56, p = 0.579, Cohen d = -0.20, 95% CI (-1.04 to 1.85)

2st

t(165.78) = 0.48, p = 0.630, Cohen d = -0.22, 95% CI (-1.36 to 2.24)

shs

1st

t(129.48) = 0.69, p = 0.491, Cohen d = -0.26, 95% CI (-2.05 to 4.25)

2st

t(166.41) = 0.98, p = 0.326, Cohen d = -0.46, 95% CI (-1.94 to 5.81)

esteem

1st

t(155.81) = -0.95, p = 0.346, Cohen d = 0.22, 95% CI (-0.84 to 0.30)

2st

t(161.37) = -0.05, p = 0.960, Cohen d = 0.02, 95% CI (-0.84 to 0.80)

mlq_search

1st

t(143.45) = 0.26, p = 0.794, Cohen d = -0.07, 95% CI (-1.11 to 1.45)

2st

t(160.09) = 0.01, p = 0.990, Cohen d = -0.00, 95% CI (-1.75 to 1.77)

mlq_presence

1st

t(135.89) = 0.15, p = 0.879, Cohen d = -0.05, 95% CI (-1.43 to 1.66)

2st

t(162.81) = 0.21, p = 0.831, Cohen d = -0.09, 95% CI (-1.79 to 2.23)

mlq

1st

t(138.14) = 0.22, p = 0.823, Cohen d = -0.07, 95% CI (-2.26 to 2.83)

2st

t(161.71) = 0.14, p = 0.891, Cohen d = -0.06, 95% CI (-3.14 to 3.61)

empower

1st

t(129.02) = 0.69, p = 0.489, Cohen d = -0.27, 95% CI (-1.04 to 2.15)

2st

t(166.60) = 0.14, p = 0.891, Cohen d = -0.06, 95% CI (-1.82 to 2.09)

ismi_resistance

1st

t(146.82) = 0.40, p = 0.693, Cohen d = -0.10, 95% CI (-0.75 to 1.12)

2st

t(159.79) = 1.00, p = 0.319, Cohen d = -0.36, 95% CI (-0.64 to 1.96)

ismi_discrimation

1st

t(134.14) = -1.93, p = 0.055, Cohen d = 0.64, 95% CI (-2.30 to 0.03)

2st

t(163.80) = -0.97, p = 0.332, Cohen d = 0.41, 95% CI (-2.23 to 0.76)

sss_affective

1st

t(133.53) = -0.63, p = 0.527, Cohen d = 0.21, 95% CI (-1.67 to 0.86)

2st

t(164.16) = -1.91, p = 0.058, Cohen d = 0.82, 95% CI (-3.19 to 0.05)

sss_behavior

1st

t(134.33) = -1.15, p = 0.254, Cohen d = 0.38, 95% CI (-2.13 to 0.57)

2st

t(163.69) = -1.61, p = 0.110, Cohen d = 0.68, 95% CI (-3.14 to 0.32)

sss_cognitive

1st

t(133.74) = -0.63, p = 0.528, Cohen d = 0.21, 95% CI (-1.75 to 0.90)

2st

t(164.03) = -2.01, p = 0.046, Cohen d = 0.86, 95% CI (-3.43 to -0.03)

sss

1st

t(130.61) = -0.88, p = 0.382, Cohen d = 0.32, 95% CI (-5.24 to 2.02)

2st

t(165.86) = -2.01, p = 0.047, Cohen d = 0.91, 95% CI (-9.11 to -0.07)

Within treatment group

recovery_stage_a

1st vs 2st

t(83.62) = 2.24, p = 0.055, Cohen d = -0.56, 95% CI (0.06 to 1.04)

recovery_stage_b

1st vs 2st

t(76.86) = 0.91, p = 0.726, Cohen d = -0.23, 95% CI (-0.60 to 1.61)

ras_confidence

1st vs 2st

t(62.59) = 2.32, p = 0.047, Cohen d = -0.62, 95% CI (0.25 to 3.33)

ras_willingness

1st vs 2st

t(62.39) = 0.62, p = 1.000, Cohen d = -0.16, 95% CI (-0.42 to 0.80)

ras_goal

1st vs 2st

t(64.40) = 2.35, p = 0.044, Cohen d = -0.62, 95% CI (0.18 to 2.23)

ras_reliance

1st vs 2st

t(61.45) = 3.31, p = 0.003, Cohen d = -0.88, 95% CI (0.54 to 2.20)

ras_domination

1st vs 2st

t(73.99) = 2.47, p = 0.032, Cohen d = -0.63, 95% CI (0.21 to 1.94)

symptom

1st vs 2st

t(56.95) = -1.38, p = 0.343, Cohen d = 0.37, 95% CI (-3.79 to 0.69)

slof_work

1st vs 2st

t(60.69) = 0.17, p = 1.000, Cohen d = -0.04, 95% CI (-1.23 to 1.46)

slof_relationship

1st vs 2st

t(59.57) = 0.88, p = 0.765, Cohen d = -0.24, 95% CI (-0.89 to 2.28)

satisfaction

1st vs 2st

t(63.35) = 0.98, p = 0.659, Cohen d = -0.26, 95% CI (-1.11 to 3.27)

mhc_emotional

1st vs 2st

t(59.66) = 0.26, p = 1.000, Cohen d = -0.07, 95% CI (-0.90 to 1.17)

mhc_social

1st vs 2st

t(63.71) = 0.38, p = 1.000, Cohen d = -0.10, 95% CI (-1.45 to 2.13)

mhc_psychological

1st vs 2st

t(62.68) = 0.66, p = 1.000, Cohen d = -0.18, 95% CI (-1.36 to 2.70)

resilisnce

1st vs 2st

t(64.63) = 2.16, p = 0.068, Cohen d = -0.57, 95% CI (0.12 to 3.04)

social_provision

1st vs 2st

t(66.35) = 0.30, p = 1.000, Cohen d = -0.08, 95% CI (-0.82 to 1.10)

els_value_living

1st vs 2st

t(64.07) = 1.07, p = 0.581, Cohen d = -0.28, 95% CI (-0.46 to 1.51)

els_life_fulfill

1st vs 2st

t(58.29) = 0.77, p = 0.888, Cohen d = -0.21, 95% CI (-0.52 to 1.16)

els

1st vs 2st

t(58.69) = 1.09, p = 0.563, Cohen d = -0.29, 95% CI (-0.70 to 2.37)

social_connect

1st vs 2st

t(59.20) = -1.93, p = 0.116, Cohen d = 0.52, 95% CI (-4.89 to 0.08)

shs_agency

1st vs 2st

t(59.88) = 1.26, p = 0.423, Cohen d = -0.34, 95% CI (-0.52 to 2.28)

shs_pathway

1st vs 2st

t(59.76) = 0.25, p = 1.000, Cohen d = -0.07, 95% CI (-0.94 to 1.22)

shs

1st vs 2st

t(58.96) = 0.88, p = 0.760, Cohen d = -0.24, 95% CI (-1.27 to 3.27)

esteem

1st vs 2st

t(79.73) = 0.74, p = 0.919, Cohen d = -0.19, 95% CI (-0.40 to 0.87)

mlq_search

1st vs 2st

t(68.60) = -0.00, p = 1.000, Cohen d = 0.00, 95% CI (-1.23 to 1.23)

mlq_presence

1st vs 2st

t(63.14) = 0.55, p = 1.000, Cohen d = -0.15, 95% CI (-0.95 to 1.67)

mlq

1st vs 2st

t(64.70) = 0.33, p = 1.000, Cohen d = -0.09, 95% CI (-1.87 to 2.62)

empower

1st vs 2st

t(58.67) = -0.47, p = 1.000, Cohen d = 0.13, 95% CI (-1.40 to 0.87)

ismi_resistance

1st vs 2st

t(71.28) = 0.97, p = 0.667, Cohen d = -0.25, 95% CI (-0.48 to 1.40)

ismi_discrimation

1st vs 2st

t(61.96) = 0.06, p = 1.000, Cohen d = -0.02, 95% CI (-0.92 to 0.97)

sss_affective

1st vs 2st

t(61.56) = -2.08, p = 0.084, Cohen d = 0.55, 95% CI (-2.07 to -0.04)

sss_behavior

1st vs 2st

t(62.09) = -1.27, p = 0.419, Cohen d = 0.34, 95% CI (-1.80 to 0.40)

sss_cognitive

1st vs 2st

t(61.70) = -1.18, p = 0.487, Cohen d = 0.31, 95% CI (-1.70 to 0.44)

sss

1st vs 2st

t(59.67) = -1.70, p = 0.188, Cohen d = 0.46, 95% CI (-5.01 to 0.40)

Within control group

recovery_stage_a

1st vs 2st

t(82.36) = 0.18, p = 1.000, Cohen d = -0.04, 95% CI (-0.44 to 0.52)

recovery_stage_b

1st vs 2st

t(75.90) = -0.52, p = 1.000, Cohen d = 0.13, 95% CI (-1.37 to 0.81)

ras_confidence

1st vs 2st

t(62.20) = 0.96, p = 0.684, Cohen d = -0.25, 95% CI (-0.79 to 2.24)

ras_willingness

1st vs 2st

t(62.00) = -2.14, p = 0.072, Cohen d = 0.56, 95% CI (-1.24 to -0.04)

ras_goal

1st vs 2st

t(63.93) = -0.88, p = 0.761, Cohen d = 0.23, 95% CI (-1.45 to 0.56)

ras_reliance

1st vs 2st

t(61.10) = 0.80, p = 0.849, Cohen d = -0.21, 95% CI (-0.49 to 1.14)

ras_domination

1st vs 2st

t(73.15) = -0.74, p = 0.928, Cohen d = 0.19, 95% CI (-1.17 to 0.54)

symptom

1st vs 2st

t(56.76) = -0.14, p = 1.000, Cohen d = 0.04, 95% CI (-2.35 to 2.05)

slof_work

1st vs 2st

t(60.36) = -0.29, p = 1.000, Cohen d = 0.08, 95% CI (-1.51 to 1.13)

slof_relationship

1st vs 2st

t(59.28) = -1.48, p = 0.288, Cohen d = 0.39, 95% CI (-2.71 to 0.40)

satisfaction

1st vs 2st

t(62.92) = 0.62, p = 1.000, Cohen d = -0.16, 95% CI (-1.49 to 2.82)

mhc_emotional

1st vs 2st

t(59.37) = 0.70, p = 0.979, Cohen d = -0.18, 95% CI (-0.66 to 1.37)

mhc_social

1st vs 2st

t(63.27) = 0.65, p = 1.000, Cohen d = -0.17, 95% CI (-1.19 to 2.33)

mhc_psychological

1st vs 2st

t(62.28) = 0.73, p = 0.930, Cohen d = -0.19, 95% CI (-1.26 to 2.72)

resilisnce

1st vs 2st

t(64.16) = 0.22, p = 1.000, Cohen d = -0.06, 95% CI (-1.28 to 1.59)

social_provision

1st vs 2st

t(65.81) = -1.31, p = 0.392, Cohen d = 0.34, 95% CI (-1.56 to 0.33)

els_value_living

1st vs 2st

t(63.62) = 0.48, p = 1.000, Cohen d = -0.13, 95% CI (-0.74 to 1.21)

els_life_fulfill

1st vs 2st

t(58.05) = 1.41, p = 0.329, Cohen d = -0.37, 95% CI (-0.24 to 1.41)

els

1st vs 2st

t(58.44) = 1.06, p = 0.591, Cohen d = -0.28, 95% CI (-0.71 to 2.30)

social_connect

1st vs 2st

t(58.93) = 1.00, p = 0.645, Cohen d = -0.26, 95% CI (-1.23 to 3.66)

shs_agency

1st vs 2st

t(59.58) = 0.08, p = 1.000, Cohen d = -0.02, 95% CI (-1.32 to 1.43)

shs_pathway

1st vs 2st

t(59.47) = 0.20, p = 1.000, Cohen d = -0.05, 95% CI (-0.96 to 1.17)

shs

1st vs 2st

t(58.69) = 0.15, p = 1.000, Cohen d = -0.04, 95% CI (-2.06 to 2.40)

esteem

1st vs 2st

t(78.64) = -0.05, p = 1.000, Cohen d = 0.01, 95% CI (-0.64 to 0.61)

mlq_search

1st vs 2st

t(67.97) = 0.26, p = 1.000, Cohen d = -0.07, 95% CI (-1.06 to 1.37)

mlq_presence

1st vs 2st

t(62.72) = 0.40, p = 1.000, Cohen d = -0.11, 95% CI (-1.02 to 1.54)

mlq

1st vs 2st

t(64.22) = 0.39, p = 1.000, Cohen d = -0.10, 95% CI (-1.78 to 2.64)

empower

1st vs 2st

t(58.41) = 0.29, p = 1.000, Cohen d = -0.08, 95% CI (-0.95 to 1.27)

ismi_resistance

1st vs 2st

t(70.54) = -0.03, p = 1.000, Cohen d = 0.01, 95% CI (-0.94 to 0.91)

ismi_discrimation

1st vs 2st

t(61.59) = -0.80, p = 0.854, Cohen d = 0.21, 95% CI (-1.30 to 0.56)

sss_affective

1st vs 2st

t(61.20) = 0.21, p = 1.000, Cohen d = -0.05, 95% CI (-0.90 to 1.10)

sss_behavior

1st vs 2st

t(61.71) = -0.12, p = 1.000, Cohen d = 0.03, 95% CI (-1.15 to 1.02)

sss_cognitive

1st vs 2st

t(61.34) = 1.29, p = 0.406, Cohen d = -0.34, 95% CI (-0.37 to 1.73)

sss

1st vs 2st

t(59.38) = 0.51, p = 1.000, Cohen d = -0.13, 95% CI (-1.98 to 3.34)

Plot

Clinical significance